Skip to main content

Ruby B. Lee

Princeton University, Computer Science, Faculty Member

Princeton University, Electrical Engineering, Faculty Member

Followers

352

Following

3

Co-authors

3

Mentions

1

Public Views

My research focus is on computer architecture, secure cloud computing, secure virtual machines, hardware-enhanced security, secure hardware, trustworthy systems, DDoS mitigation, multimedia architecture and new media.

less

University of Wollongong

David Pierre Leibovitz

Carleton University

University of Liverpool online programme with Laureate

Kansas State University

Armando Marques-Guedes

UNL - New University of Lisbon

Derrick de Kerckhove

University of Toronto

Qusay F. Hassan

Roshan Chitrakar

Nepal College of Information Technology

Graduate Center of the City University of New York

Anna University

InterestsView All (12)

Uploads

Papers by Ruby B. Lee

Mapping of Application Software to the Multimedia Instructions of GeneralPurpose Microprocessors

by Larry McMahan and Ruby B. Lee

This paper describes how media processing programs may be accelerated by using the multimedia ins... more This paper describes how media processing programs may be accelerated by using the multimedia instruction extensions that have been added to general-purpose microprocessors. As a concrete example, it describes MAX2, a minimalist, second-generation set of multimedia instructions included in the PA-RISC 2.0 processor architecture. MAX2 implements subword parallel instructions, which utilize the microprocessor's 64-bit wide datapaths to process multiple pieces of lower-precision data in parallel. It also includes innovative, new instructions like Mix, which are very useful for matrix transpose and other common data rearrangements. The paper examines some typical multimedia kernels, like Block Match, Matrix Transpose, Box Filter and the IDCT, coded with and without the MAX2 instructions, to illustrate programming techniques for exploiting subword parallelism and superscalar instruction parallelism. The kernels using MAX2 show significant speedups in execution time, and more efficient utilization of the processor's resources.

Position Paper: Consider Hardware-enhanced Defenses for Rootkit Attacks

by Guangyuan Hu and Ruby B. Lee

Hardware and Architectural Support for Security and Privacy, 2020

Rootkits are malware that attempt to compromise the system's functionalities while hiding their e... more Rootkits are malware that attempt to compromise the system's functionalities while hiding their existence. Various rootkits have been proposed as well as different software defenses, but only very few hardware defenses. We position hardware-enhanced rootkit defenses as an interesting research opportunity for computer architects, especially as many new hardware defenses for speculative execution attacks are being actively considered. We first describe different techniques used by rootkits and their prime targets in the operating system. We then try to shed insights on what the main challenges are in providing a rootkit defense, and how these may be overcome. We show how a hypervisor-based defense can be implemented, and provide a full prototype implementation in an open-source cloud computing platform, OpenStack. We evaluate the performance overhead of different defense mechanisms. Finally, we point to some research opportunities for enhancing resilience to rootkit-like attacks in the hardware architecture.

New Models for Understanding and Reasoning about Speculative Execution Attacks

by Guangyuan Hu and Ruby B. Lee

2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2021

Spectre and Meltdown attacks and their variants exploit hardware performance optimization feature... more Spectre and Meltdown attacks and their variants exploit hardware performance optimization features to cause security breaches. Secret information is accessed and leaked through covert or side channels. New attack variants keep appearing and we do not have a systematic way to capture the critical characteristics of these attacks and evaluate why they succeed or fail. In this paper, we provide a new attack-graph model for reasoning about speculative execution attacks. We model attacks as ordered dependency graphs, and prove that a race condition between two nodes can occur if there is a missing dependency edge between them. We define a new concept, "security dependency", between a resource access and its prior authorization operation. We show that a missing security dependency is equivalent to a race condition between authorization and access, which is a root cause of speculative execution attacks. We show detailed examples of how our attack graph models the Spectre and Meltdown attacks, and is generalizable to all the attack variants published so far. This attack model is also very useful for identifying new attacks and for generalizing defense strategies. We identify several defense strategies with different performance-security tradeoffs. We show that the defenses proposed so far all fit under one of our defense strategies. We also explain how attack graphs can be constructed and point to this as promising future work for tool designers.

Smartphone Impostor Detection with Built-in Sensors and Deep Learning

by Guangyuan Hu and Ruby B. Lee

arXiv (Cornell University), Feb 10, 2020

In this paper, we show that sensor-based impostor detection with deep learning can achieve excell... more In this paper, we show that sensor-based impostor detection with deep learning can achieve excellent impostor detection accuracy at lower hardware cost compared to past work on sensor-based user authentication (the inverse problem) which used more conventional machine learning algorithms. While these methods use other smartphone users' sensor data to build the (user, non-user) classification models, we go further to show that using only the legitimate user's sensor data can still achieve very good accuracy while preserving the privacy of the user's sensor data (behavioral biometrics). For this use case, a key contribution is showing that the detection accuracy of a Recurrent Neural Network (RNN) deep learning model can be significantly improved by comparing prediction error distributions. This requires generating and comparing empirical probability distributions, which we show in an efficient hardware design. Another novel contribution is in the design of SID (Smartphone impostor Detection), a minimalist hardware accelerator that can be integrated into future smartphones for efficient impostor detection for different scenarios. Our SID module can implement many common Machine Learning and Deep Learning algorithms. SID is also scalable in parallelism and performance and easy to program. We show an FPGA prototype of SID, which can provide more than enough performance for real-time impostor detection, with very low hardware complexity and power consumption (one to two orders of magnitude less than related performance-oriented FPGA accelerators). We also show that the FPGA implementation of SID consumes 64.41X less energy than an implementation using the CPU with a GPU.

SoK: Hardware Defenses Against Speculative Execution Attacks

by Guangyuan Hu and Ruby B. Lee

2021 International Symposium on Secure and Private Execution Environment Design (SEED), 2021

Speculative execution attacks leverage the speculative and out-of-order execution features in mod... more Speculative execution attacks leverage the speculative and out-of-order execution features in modern computer processors to access secret data or execute code that should not be executed. Secret information can then be leaked through a covert channel. While software patches can be installed for mitigation on existing hardware, these solutions can incur big performance overhead. Hardware mitigation is being studied extensively by the computer architecture community. It has the benefit of preserving software compatibility and the potential for much smaller performance overhead than software solutions. This paper presents a systematization of the hardware defenses against speculative execution attacks that have been proposed. We show that speculative execution attacks consist of 6 critical attack steps. We propose defense strategies, each of which prevents a critical attack step from happening, thus preventing the attack from succeeding. We then summarize 20 hardware defenses and overhead-reducing features that have been proposed. We show that each defense proposed can be classified under one of our defense strategies, which also explains why it can thwart the attack from succeeding. We discuss the scope of the defenses, their performance overhead, and the security-performance trade-offs that can be made.

CloudShield: Real-time Anomaly Detection in the Cloud

by Guangyuan Hu and Ruby B. Lee

Power-Grid Controller Anomaly Detection with Enhanced Temporal Deep Learning

by Guangyuan Hu and Ruby B. Lee

arXiv (Cornell University), Jun 18, 2018

Controllers of security-critical cyber-physical systems, like the power grid, are a very importan... more Controllers of security-critical cyber-physical systems, like the power grid, are a very important class of computer systems. Attacks against the control code of a power-grid system, especially zero-day attacks, can be catastrophic. Earlier detection of the anomalies can prevent further damage. However, detecting zero-day attacks is extremely challenging because they have no known code and have unknown behavior. Furthermore, if data collected from the controller is transferred to a server through networks for analysis and detection of anomalous behavior, this creates a very large attack surface and also delays detection. In order to address this problem, we propose Reconstruction Error Distribution (RED) of Hardware Performance Counters (HPCs), and a data-driven defense system based on it. Specifically, we first train a temporal deep learning model, using only normal HPC readings from legitimate processes that run daily in these power-grid systems, to model the normal behavior of the power-grid controller. Then, we run this model using real-time data from commonly available HPCs. We use the proposed RED to enhance the temporal deep learning detection of anomalous behavior, by estimating distribution deviations from the normal behavior with an effective statistical test. Experimental results on a real power-grid controller show that we can detect anomalous behavior with high accuracy (>99.9%), nearly zero false positives and short (<360ms) latency.

New Models for Understanding and Reasoning about Speculative Execution Attacks

by Guangyuan Hu and Ruby B. Lee

arXiv (Cornell University), Sep 16, 2020

Improving Performance for MPEG Players

Compcon, 1996

Micro-architecture issues of predicated execution

The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003

SecureCore West (Poster)

Enables dynamic, "transient trust" security policies for achieving the appropriate availability o... more

Multipath Key Establishment under Byzantine Attacks in Wireless Ad Hoc Networks

Secure communications in wireless ad hoc networks are protected by setting up end-to-end secret k... more Secure communications in wireless ad hoc networks are protected by setting up end-to-end secret keys for commu- nicating node pairs. Secret keys can be provided by pre-loading shared secrets (e.g. a set of potential keys or keying informa- tion) into nodes prior to deployment. However, due to physical limitations of nodes and network scalability requirements, this key pre-distribution approach is not able to achieve full key- connectivity for all communicating pairs. Therefore, on-demand key establishment, in which pairwise secret keys are derived by exchanging multiple keying messages among wireless nodes, becomes necessary. In this paper, we develop a theoretical framework for the on- demand key establishment approach. Our contributions include a novel security metric, which we call a Byzantine resilience vector, to quantify the resilience of any key establishment scheme against Byzantine (arbitrary) attacks. Our analysis shows that previous key establishment schemes are vulnerabl...

Attacking and Protecting Data Privacy in Edge–Cloud Collaborative Inference Systems

IEEE Internet of Things Journal, 2020

Benefiting from the advance of Deep Learning technology, IoT devices and systems are becoming mor... more Benefiting from the advance of Deep Learning technology, IoT devices and systems are becoming more intelligent and multi-functional. They are expected to run various Deep Learning inference tasks with high efficiency and performance. This requirement is challenged by the mismatch between the limited computing capability of edge devices and large-scale Deep Neural Networks. Edge-cloud collaborative systems are then introduced to mitigate this conflict, enabling resource-constrained IoT devices to host arbitrary Deep Learning applications. However, the introduction of third-party clouds can bring potential privacy issues to edge computing. In this paper, we conduct a systematic study about the opportunities of attacking and protecting the privacy of edge-cloud collaborative systems. Our contributions are twofold: (1) we first devise a set of new attacks for an untrusted cloud to recover arbitrary inputs fed into the system, even if the attacker has no access to the edge device's data or computations, or permissions to query this system. (2) We empirically demonstrate that solutions that add noise fail to defeat our proposed attacks, and then propose two more effective defense methods. This provides insights and guidelines to develop more privacy-preserving collaborative systems and algorithms.

SoK: Hardware Defenses Against Speculative Execution Attacks

2021 International Symposium on Secure and Private Execution Environment Design (SEED), 2021

Speculative execution attacks leverage the speculative and out-of-order execution features in mod... more Speculative execution attacks leverage the speculative and out-of-order execution features in modern computer processors to access secret data or execute code that should not be executed. Secret information can then be leaked through a covert channel. While software patches can be installed for mitigation on existing hardware, these solutions can incur big performance overhead. Hardware mitigation is being studied extensively by the computer architecture community. It has the benefit of preserving software compatibility and the potential for much smaller performance overhead than software solutions. This paper presents a systematization of the hardware defenses against speculative execution attacks that have been proposed. We show that speculative execution attacks consist of 6 critical attack steps. We propose defense strategies, each of which prevents a critical attack step from happening, thus preventing the attack from succeeding. We then summarize 20 hardware defenses and overhead-reducing features that have been proposed. We show that each defense proposed can be classified under one of our defense strategies, which also explains why it can thwart the attack from succeeding. We discuss the scope of the defenses, their performance overhead, and the security-performance trade-offs that can be made.

CloudRadar: A Real-Time Side-Channel Attack Detection System in Clouds

Research in Attacks, Intrusions, and Defenses, 2016

We present CloudRadar , a system to detect, and hence mitigate, cache-based side-channel attacks ... more We present CloudRadar , a system to detect, and hence mitigate, cache-based side-channel attacks in multi-tenant cloud systems. CloudRadar operates by correlating two events: first, it exploits signaturebased detection to identify when the protected virtual machine (VM) executes a cryptographic application; at the same time, it uses anomalybased detection techniques to monitor the co-located VMs to identify abnormal cache behaviors that are typical during cache-based side-channel attacks. We show that correlation in the occurrence of these two events o↵er strong evidence of side-channel attacks. Compared to other work on side-channel defenses, CloudRadar has the following advantages: first, CloudRadar focuses on the root causes of cache-based side-channel attacks and hence is hard to evade using metamorphic attack code, while maintaining a low false positive rate. Second, CloudRadar is designed as a lightweight patch to existing cloud systems, which does not require new hardware support, or any hypervisor, operating system, application modifications. Third, CloudRadar provides real-time protection and can detect side-channel attacks within the order of milliseconds. We demonstrate a prototype implementation of CloudRadar in the Open-Stack cloud framework. Our evaluation suggests CloudRadar achieves negligible performance overhead with high detection accuracy.

Exploration and evaluation of PLX floating-point instructions and implementations for 3D graphics

Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004.

PLX FP is a floating-point instruction set architecture (ISA) extension to PLX that is designed f... more PLX FP is a floating-point instruction set architecture (ISA) extension to PLX that is designed for fast and efficient 3D graphics processing. In this paper, we explore the implementation and performance of the fundamental functional unit for PLX FP, the floating-point multiply-accumulate (FMAC) functional unit. We present simulation and synthesis results for several implementations with increasingly powerful sets of instructions, to compare area and delay tradeoffs. We also evaluate the performance tradeoffs with examples taken from the 3D graphics processing pipeline.

Scoping security issues for interactive grids

The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003

Grid computing allows flexible resource sharing among geographically distributed computing resour... more Grid computing allows flexible resource sharing among geographically distributed computing resources in multiple administrative domains. Virtualization of resources allows jobs to be run on remote resources participating in a Grid. While this computing paradigm has been used primarily for batch jobs, we study interactive Grid applications rich in graphics and multimedia such as scientific visualization and digital content creation. A host of security issues need to be addressed for such Interactive Grids to gain acceptance, particularly in industry. The purpose of this paper is to scope these security issues. The Grid Security Infrastructure (GSI), a component of the Globus Toolkit [1], creates Grid credentials for every user and resource. We describe how this may be extended to securely set up an interactive session on a remote host, and the additional security issues associated with interactive session management. We propose controlled shell and controlled desktop mechanisms that restrict the user to execute only authorized commands and applications, and controlled user and super-user accounts that customize the shell and desktop using policy files. We also propose a new approach to scoping the security needs of Grid systems by defining three generic scenarios: mutual trust, partial trust and mutual distrust. New security issues arise when the user may not be trusted, or the user and the host computer's owner are mutually suspicious.

ACM SIGARCH Computer Architecture News, 2010

Cloud computing is a disruptive trend that is changing the way we use computers. The key underlyi... more Cloud computing is a disruptive trend that is changing the way we use computers. The key underlying technology in cloud infrastructures is virtualization -- so much so that many consider virtualization to be one of the key features rather than simply an implementation detail. Unfortunately, the use of virtualization is the source of a significant security concern. Because multiple virtual machines run on the same server and since the virtualization layer plays a considerable role in the operation of a virtual machine, a malicious party has the opportunity to attack the virtualization layer. A successful attack would give the malicious party control over the all-powerful virtualization layer, potentially compromising the confidentiality and integrity of the software and data of any virtual machine. In this paper we propose removing the virtualization layer, while retaining the key features enabled by virtualization. Our NoHype architecture, named to indicate the removal of the hyperv...

Architecture for a Non-Copyable Disk (NCdisk) Using a Secret-Protection (SP) SoC Solution

2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers, 2007

Piracy of copyrighted digital contents, such as movies and music is rampant in cyberspace. A piec... more Piracy of copyrighted digital contents, such as movies and music is rampant in cyberspace. A piece of digital material may be repeatedly copied and proliferated throughout the Internet with ease. We examined both software and hardware vulnerabilities in existing digital copy-protection methods. As a result, we propose a non-copyable disk (NCdisk) that makes it significantly harder for digital contents to be copied. Any digital content written onto the NCdisk can only be read through a predefined set of outputs of the NCdisk, and the original plaintext digital form may never be read out of the NCdisk. We add a minimal set of components based on the Secret-Protection (SP) architecture to the existing disk's SoC chipset to attribute the disk with the non-copyable property. We further present the security protocol to be used along with the NCdisk to provide a copy-protected digital movie download scenario.

Eliminating the hypervisor attack surface for a more secure cloud

Proceedings of the 18th ACM conference on Computer and communications security - CCS '11, 2011

Cloud computing is quickly becoming the platform of choice for many web services. Virtualization ... more

Mapping of Application Software to the Multimedia Instructions of GeneralPurpose Microprocessors

by Larry McMahan and Ruby B. Lee

This paper describes how media processing programs may be accelerated by using the multimedia ins... more This paper describes how media processing programs may be accelerated by using the multimedia instruction extensions that have been added to general-purpose microprocessors. As a concrete example, it describes MAX2, a minimalist, second-generation set of multimedia instructions included in the PA-RISC 2.0 processor architecture. MAX2 implements subword parallel instructions, which utilize the microprocessor's 64-bit wide datapaths to process multiple pieces of lower-precision data in parallel. It also includes innovative, new instructions like Mix, which are very useful for matrix transpose and other common data rearrangements. The paper examines some typical multimedia kernels, like Block Match, Matrix Transpose, Box Filter and the IDCT, coded with and without the MAX2 instructions, to illustrate programming techniques for exploiting subword parallelism and superscalar instruction parallelism. The kernels using MAX2 show significant speedups in execution time, and more efficient utilization of the processor's resources.

Position Paper: Consider Hardware-enhanced Defenses for Rootkit Attacks

by Guangyuan Hu and Ruby B. Lee

Hardware and Architectural Support for Security and Privacy, 2020

Rootkits are malware that attempt to compromise the system's functionalities while hiding their e... more Rootkits are malware that attempt to compromise the system's functionalities while hiding their existence. Various rootkits have been proposed as well as different software defenses, but only very few hardware defenses. We position hardware-enhanced rootkit defenses as an interesting research opportunity for computer architects, especially as many new hardware defenses for speculative execution attacks are being actively considered. We first describe different techniques used by rootkits and their prime targets in the operating system. We then try to shed insights on what the main challenges are in providing a rootkit defense, and how these may be overcome. We show how a hypervisor-based defense can be implemented, and provide a full prototype implementation in an open-source cloud computing platform, OpenStack. We evaluate the performance overhead of different defense mechanisms. Finally, we point to some research opportunities for enhancing resilience to rootkit-like attacks in the hardware architecture.

New Models for Understanding and Reasoning about Speculative Execution Attacks

by Guangyuan Hu and Ruby B. Lee

2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2021

Spectre and Meltdown attacks and their variants exploit hardware performance optimization feature... more Spectre and Meltdown attacks and their variants exploit hardware performance optimization features to cause security breaches. Secret information is accessed and leaked through covert or side channels. New attack variants keep appearing and we do not have a systematic way to capture the critical characteristics of these attacks and evaluate why they succeed or fail. In this paper, we provide a new attack-graph model for reasoning about speculative execution attacks. We model attacks as ordered dependency graphs, and prove that a race condition between two nodes can occur if there is a missing dependency edge between them. We define a new concept, "security dependency", between a resource access and its prior authorization operation. We show that a missing security dependency is equivalent to a race condition between authorization and access, which is a root cause of speculative execution attacks. We show detailed examples of how our attack graph models the Spectre and Meltdown attacks, and is generalizable to all the attack variants published so far. This attack model is also very useful for identifying new attacks and for generalizing defense strategies. We identify several defense strategies with different performance-security tradeoffs. We show that the defenses proposed so far all fit under one of our defense strategies. We also explain how attack graphs can be constructed and point to this as promising future work for tool designers.

Smartphone Impostor Detection with Built-in Sensors and Deep Learning

by Guangyuan Hu and Ruby B. Lee

arXiv (Cornell University), Feb 10, 2020

In this paper, we show that sensor-based impostor detection with deep learning can achieve excell... more In this paper, we show that sensor-based impostor detection with deep learning can achieve excellent impostor detection accuracy at lower hardware cost compared to past work on sensor-based user authentication (the inverse problem) which used more conventional machine learning algorithms. While these methods use other smartphone users' sensor data to build the (user, non-user) classification models, we go further to show that using only the legitimate user's sensor data can still achieve very good accuracy while preserving the privacy of the user's sensor data (behavioral biometrics). For this use case, a key contribution is showing that the detection accuracy of a Recurrent Neural Network (RNN) deep learning model can be significantly improved by comparing prediction error distributions. This requires generating and comparing empirical probability distributions, which we show in an efficient hardware design. Another novel contribution is in the design of SID (Smartphone impostor Detection), a minimalist hardware accelerator that can be integrated into future smartphones for efficient impostor detection for different scenarios. Our SID module can implement many common Machine Learning and Deep Learning algorithms. SID is also scalable in parallelism and performance and easy to program. We show an FPGA prototype of SID, which can provide more than enough performance for real-time impostor detection, with very low hardware complexity and power consumption (one to two orders of magnitude less than related performance-oriented FPGA accelerators). We also show that the FPGA implementation of SID consumes 64.41X less energy than an implementation using the CPU with a GPU.

SoK: Hardware Defenses Against Speculative Execution Attacks

by Guangyuan Hu and Ruby B. Lee

2021 International Symposium on Secure and Private Execution Environment Design (SEED), 2021

Speculative execution attacks leverage the speculative and out-of-order execution features in mod... more Speculative execution attacks leverage the speculative and out-of-order execution features in modern computer processors to access secret data or execute code that should not be executed. Secret information can then be leaked through a covert channel. While software patches can be installed for mitigation on existing hardware, these solutions can incur big performance overhead. Hardware mitigation is being studied extensively by the computer architecture community. It has the benefit of preserving software compatibility and the potential for much smaller performance overhead than software solutions. This paper presents a systematization of the hardware defenses against speculative execution attacks that have been proposed. We show that speculative execution attacks consist of 6 critical attack steps. We propose defense strategies, each of which prevents a critical attack step from happening, thus preventing the attack from succeeding. We then summarize 20 hardware defenses and overhead-reducing features that have been proposed. We show that each defense proposed can be classified under one of our defense strategies, which also explains why it can thwart the attack from succeeding. We discuss the scope of the defenses, their performance overhead, and the security-performance trade-offs that can be made.

CloudShield: Real-time Anomaly Detection in the Cloud

by Guangyuan Hu and Ruby B. Lee

Power-Grid Controller Anomaly Detection with Enhanced Temporal Deep Learning

by Guangyuan Hu and Ruby B. Lee

arXiv (Cornell University), Jun 18, 2018

Controllers of security-critical cyber-physical systems, like the power grid, are a very importan... more Controllers of security-critical cyber-physical systems, like the power grid, are a very important class of computer systems. Attacks against the control code of a power-grid system, especially zero-day attacks, can be catastrophic. Earlier detection of the anomalies can prevent further damage. However, detecting zero-day attacks is extremely challenging because they have no known code and have unknown behavior. Furthermore, if data collected from the controller is transferred to a server through networks for analysis and detection of anomalous behavior, this creates a very large attack surface and also delays detection. In order to address this problem, we propose Reconstruction Error Distribution (RED) of Hardware Performance Counters (HPCs), and a data-driven defense system based on it. Specifically, we first train a temporal deep learning model, using only normal HPC readings from legitimate processes that run daily in these power-grid systems, to model the normal behavior of the power-grid controller. Then, we run this model using real-time data from commonly available HPCs. We use the proposed RED to enhance the temporal deep learning detection of anomalous behavior, by estimating distribution deviations from the normal behavior with an effective statistical test. Experimental results on a real power-grid controller show that we can detect anomalous behavior with high accuracy (>99.9%), nearly zero false positives and short (<360ms) latency.

New Models for Understanding and Reasoning about Speculative Execution Attacks

by Guangyuan Hu and Ruby B. Lee

arXiv (Cornell University), Sep 16, 2020

Improving Performance for MPEG Players

Compcon, 1996

Micro-architecture issues of predicated execution

The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003

SecureCore West (Poster)

Enables dynamic, "transient trust" security policies for achieving the appropriate availability o... more

Multipath Key Establishment under Byzantine Attacks in Wireless Ad Hoc Networks

Secure communications in wireless ad hoc networks are protected by setting up end-to-end secret k... more Secure communications in wireless ad hoc networks are protected by setting up end-to-end secret keys for commu- nicating node pairs. Secret keys can be provided by pre-loading shared secrets (e.g. a set of potential keys or keying informa- tion) into nodes prior to deployment. However, due to physical limitations of nodes and network scalability requirements, this key pre-distribution approach is not able to achieve full key- connectivity for all communicating pairs. Therefore, on-demand key establishment, in which pairwise secret keys are derived by exchanging multiple keying messages among wireless nodes, becomes necessary. In this paper, we develop a theoretical framework for the on- demand key establishment approach. Our contributions include a novel security metric, which we call a Byzantine resilience vector, to quantify the resilience of any key establishment scheme against Byzantine (arbitrary) attacks. Our analysis shows that previous key establishment schemes are vulnerabl...

Attacking and Protecting Data Privacy in Edge–Cloud Collaborative Inference Systems

IEEE Internet of Things Journal, 2020

Benefiting from the advance of Deep Learning technology, IoT devices and systems are becoming mor... more Benefiting from the advance of Deep Learning technology, IoT devices and systems are becoming more intelligent and multi-functional. They are expected to run various Deep Learning inference tasks with high efficiency and performance. This requirement is challenged by the mismatch between the limited computing capability of edge devices and large-scale Deep Neural Networks. Edge-cloud collaborative systems are then introduced to mitigate this conflict, enabling resource-constrained IoT devices to host arbitrary Deep Learning applications. However, the introduction of third-party clouds can bring potential privacy issues to edge computing. In this paper, we conduct a systematic study about the opportunities of attacking and protecting the privacy of edge-cloud collaborative systems. Our contributions are twofold: (1) we first devise a set of new attacks for an untrusted cloud to recover arbitrary inputs fed into the system, even if the attacker has no access to the edge device's data or computations, or permissions to query this system. (2) We empirically demonstrate that solutions that add noise fail to defeat our proposed attacks, and then propose two more effective defense methods. This provides insights and guidelines to develop more privacy-preserving collaborative systems and algorithms.

SoK: Hardware Defenses Against Speculative Execution Attacks

2021 International Symposium on Secure and Private Execution Environment Design (SEED), 2021

Speculative execution attacks leverage the speculative and out-of-order execution features in mod... more Speculative execution attacks leverage the speculative and out-of-order execution features in modern computer processors to access secret data or execute code that should not be executed. Secret information can then be leaked through a covert channel. While software patches can be installed for mitigation on existing hardware, these solutions can incur big performance overhead. Hardware mitigation is being studied extensively by the computer architecture community. It has the benefit of preserving software compatibility and the potential for much smaller performance overhead than software solutions. This paper presents a systematization of the hardware defenses against speculative execution attacks that have been proposed. We show that speculative execution attacks consist of 6 critical attack steps. We propose defense strategies, each of which prevents a critical attack step from happening, thus preventing the attack from succeeding. We then summarize 20 hardware defenses and overhead-reducing features that have been proposed. We show that each defense proposed can be classified under one of our defense strategies, which also explains why it can thwart the attack from succeeding. We discuss the scope of the defenses, their performance overhead, and the security-performance trade-offs that can be made.

CloudRadar: A Real-Time Side-Channel Attack Detection System in Clouds

Research in Attacks, Intrusions, and Defenses, 2016

We present CloudRadar , a system to detect, and hence mitigate, cache-based side-channel attacks ... more We present CloudRadar , a system to detect, and hence mitigate, cache-based side-channel attacks in multi-tenant cloud systems. CloudRadar operates by correlating two events: first, it exploits signaturebased detection to identify when the protected virtual machine (VM) executes a cryptographic application; at the same time, it uses anomalybased detection techniques to monitor the co-located VMs to identify abnormal cache behaviors that are typical during cache-based side-channel attacks. We show that correlation in the occurrence of these two events o↵er strong evidence of side-channel attacks. Compared to other work on side-channel defenses, CloudRadar has the following advantages: first, CloudRadar focuses on the root causes of cache-based side-channel attacks and hence is hard to evade using metamorphic attack code, while maintaining a low false positive rate. Second, CloudRadar is designed as a lightweight patch to existing cloud systems, which does not require new hardware support, or any hypervisor, operating system, application modifications. Third, CloudRadar provides real-time protection and can detect side-channel attacks within the order of milliseconds. We demonstrate a prototype implementation of CloudRadar in the Open-Stack cloud framework. Our evaluation suggests CloudRadar achieves negligible performance overhead with high detection accuracy.

Exploration and evaluation of PLX floating-point instructions and implementations for 3D graphics

Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004.

PLX FP is a floating-point instruction set architecture (ISA) extension to PLX that is designed f... more PLX FP is a floating-point instruction set architecture (ISA) extension to PLX that is designed for fast and efficient 3D graphics processing. In this paper, we explore the implementation and performance of the fundamental functional unit for PLX FP, the floating-point multiply-accumulate (FMAC) functional unit. We present simulation and synthesis results for several implementations with increasingly powerful sets of instructions, to compare area and delay tradeoffs. We also evaluate the performance tradeoffs with examples taken from the 3D graphics processing pipeline.

Scoping security issues for interactive grids

The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003

Grid computing allows flexible resource sharing among geographically distributed computing resour... more Grid computing allows flexible resource sharing among geographically distributed computing resources in multiple administrative domains. Virtualization of resources allows jobs to be run on remote resources participating in a Grid. While this computing paradigm has been used primarily for batch jobs, we study interactive Grid applications rich in graphics and multimedia such as scientific visualization and digital content creation. A host of security issues need to be addressed for such Interactive Grids to gain acceptance, particularly in industry. The purpose of this paper is to scope these security issues. The Grid Security Infrastructure (GSI), a component of the Globus Toolkit [1], creates Grid credentials for every user and resource. We describe how this may be extended to securely set up an interactive session on a remote host, and the additional security issues associated with interactive session management. We propose controlled shell and controlled desktop mechanisms that restrict the user to execute only authorized commands and applications, and controlled user and super-user accounts that customize the shell and desktop using policy files. We also propose a new approach to scoping the security needs of Grid systems by defining three generic scenarios: mutual trust, partial trust and mutual distrust. New security issues arise when the user may not be trusted, or the user and the host computer's owner are mutually suspicious.

ACM SIGARCH Computer Architecture News, 2010

Cloud computing is a disruptive trend that is changing the way we use computers. The key underlyi... more Cloud computing is a disruptive trend that is changing the way we use computers. The key underlying technology in cloud infrastructures is virtualization -- so much so that many consider virtualization to be one of the key features rather than simply an implementation detail. Unfortunately, the use of virtualization is the source of a significant security concern. Because multiple virtual machines run on the same server and since the virtualization layer plays a considerable role in the operation of a virtual machine, a malicious party has the opportunity to attack the virtualization layer. A successful attack would give the malicious party control over the all-powerful virtualization layer, potentially compromising the confidentiality and integrity of the software and data of any virtual machine. In this paper we propose removing the virtualization layer, while retaining the key features enabled by virtualization. Our NoHype architecture, named to indicate the removal of the hyperv...

Architecture for a Non-Copyable Disk (NCdisk) Using a Secret-Protection (SP) SoC Solution

2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers, 2007

Piracy of copyrighted digital contents, such as movies and music is rampant in cyberspace. A piec... more Piracy of copyrighted digital contents, such as movies and music is rampant in cyberspace. A piece of digital material may be repeatedly copied and proliferated throughout the Internet with ease. We examined both software and hardware vulnerabilities in existing digital copy-protection methods. As a result, we propose a non-copyable disk (NCdisk) that makes it significantly harder for digital contents to be copied. Any digital content written onto the NCdisk can only be read through a predefined set of outputs of the NCdisk, and the original plaintext digital form may never be read out of the NCdisk. We add a minimal set of components based on the Secret-Protection (SP) architecture to the existing disk's SoC chipset to attribute the disk with the non-copyable property. We further present the security protocol to be used along with the NCdisk to provide a copy-protected digital movie download scenario.

Eliminating the hypervisor attack surface for a more secure cloud

Proceedings of the 18th ACM conference on Computer and communications security - CCS '11, 2011

Cloud computing is quickly becoming the platform of choice for many web services. Virtualization ... more